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harness-meta

Triage retrospective harness improvement proposals into adoption, rejection, or removal paths.

18|Updated Feb 14, 2020
Search Tags:#feedback#pull request#retrospective#triage#harness#dry-run
One-click install
npx skills add https://github.com/subroh0508/colormaster --skill harness-meta
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: harness-meta
Source: https://github.com/subroh0508/colormaster/tree/main/.claude/skills/harness-meta
Command: npx skills add https://github.com/subroh0508/colormaster --skill harness-meta

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill turns scattered retrospective improvement notes into a disciplined follow-up process, so teams can decide what to adopt, skip, or remove without losing context or auditability.

Core Features & Use Cases

  • Proposal Triage: Classifies harness improvement suggestions into adoption, deferral, or removal paths using the defined criteria.
  • PR and Feedback Orchestration: Creates the right follow-up action, whether that is opening a change PR, adding feedback to the source learning file, or handling a staged removal.
  • Safety and Traceability: Preserves links to source learning files, applies dry-run checks when required, and keeps the workflow aligned with repository rules and review gates.
  • Use Case: A batch of retrospective notes arrives from several pull requests, and this Skill consolidates them into actionable outcomes with consistent reasoning.

Quick Start

Ask the harness-meta skill to review the specified learning files and classify each harness improvement proposal into adopt, skip, or remove with the appropriate follow-up action.

Frequently Asked Questions about harness-meta

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I triage retrospective improvement proposals into pull requests?▼

Triage retrospective improvement proposals by classifying each harness idea into adoption, rejection, or removal paths, then orchestrating the corresponding pull request or feedback update to ensure actionable outcomes.

What is the best way to consolidate retrospective notes from multiple pull requests?▼

Consolidating retrospective notes from multi-PR learning batches involves evaluating each duplicate proposal against strict harness-meta criteria and routing items to adoption, deferral, or staged removal while preserving traceability.

Can I perform a dry-run check before applying harness retrospective changes?▼

Yes, you can perform a dry-run check before applying harness retrospective changes. The workflow applies dry-run gating when required to validate proposals safely before opening any change pull requests.

How do I handle staged removal of harness improvements without losing traceability?▼

Handle staged removal of harness improvements by executing staged removal workflows that preserve links to source learning files and apply cooldown checks, ensuring full traceability throughout the removal process.

Does the triage workflow support adding feedback to the source learning file?▼

Yes, the triage workflow supports adding feedback directly to the source learning file. When a proposal is rejected or deferred, the workflow updates the source file instead of opening a pull request.

When do I need to apply cooldown checks during retrospective triage?▼

Apply cooldown checks during retrospective triage when processing staged removal workflows. These checks ensure that removing an adopted harness improvement respects evaluation gates and preserves repository rules before completion.

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